Detection of red lesions in digital fundus images

This paper presents an efficient approach for automatic detection of red lesions in ocular fundus images. The approach uses the intensity information from red and green channels of the same retinal image to correct non-uniform illumination in color fundus images. Matched filtering is utilized to enhance the contrast of red lesions against the background. The enhanced red lesions are then segmented by employing relative entropy based thresholding which can well maintain the spatial structure of the red lesion segments. Then morphological top-hat transformation is used to suppress the enhanced vasculature. SVIvIs are used to classify the candidate red lesions from other dark segments. Experimental evaluation of the proposed approach demonstrates superior performance over other red lesion detection algorithms recently reported in the literature.